Dr. Yong Li
Department of Civil & Environmental Engineering
University of Alberta, Edmonton, Canada
Dr. Li is fascinated in developing and applying (1) mechanics-based advanced structural models, and (2) probabilistic and statistical methods to engineering risk/reliability problems in the field of structural engineering. This serves to assist decision-making in the process of probability-based design, retrofit, and maintenance of a wide range of structures (e.g., concrete bridges, masonry buildings, steel pipelines, etc.) in the face of uncertainty. He is also interested in inverse engineering problems (e.g., structural design optimization in earthquake engineering, nonlinear FE model updating using field-recorded and experimental data, data-driven model learning problems, probabilistic diagnosis and prognosis for structural system and mechanical equipment).
Ph.D. in Structural Engineering, UC San Digo
M.Sc. in Applied Mathematics, UC San Diego
M.Sc. in Civil Engineering, Tsinghua University
Postdoctoral Fellow, UC San Diego
Assistant Professor, University of Alberta
Director of Institute of Interdisciplinary Scientists
Faculty member of Steel Center at UoA
Faculty member of Masonry Center at UoA
Structural and geotechnical earthquake engineering: performance-based engineering, design optimization for structures with innovative devices (e.g., isolation, dampers, etc.)
Mechanics-based nonlinear FE modeling: Concrete/masonry/steel bridge/building structures, pipelines, soil-structure-interaction, etc.
Probabilistic modeling: Stochastic modeling of natural hazard loads, traffic loads, deterioration processes, etc.
Structural reliability and risk: Uncertainty propagation, risk quantification, probability-based code calibration and design optimization.
System identification: Statistical structural health monitoring, nonlinear finite element model updating, etc.
Bayesian statistical methods: Bayesian model calibration, validation with error assessment, and uncertainty quantification
Performance assessment, diagnostics, prognosis of degraded systems: Structural deterioration (corrosion), fatigue, etc.
CIV E 295 Civil Engr. Analysis
This course aims to cover the fundamental numerical analysis methods to solve civil engineering problems. It is primarily designed for undergraduate students, who are interested in enhance their problem solving skills by self-implemented computer programs or available computer tools.
CIV E 372 Structural Analysis
This course aims to cover the principles of classical structural analysis and help students build engineering intuitions about structures. It is primarily designed for undergraduate students, who are interested in: (1) taking advanced structural analysis and design courses in the coming terms; and (2) seeking an industry position with required professional skills on design, modeling, and analysis.
CIV E 660 Advanced Structural Analysis (Fall Term)
This course aims to cover the principles of modern matrix structural analysis of frame structures in Finite Element software packages. It is primarily designed for graduate students, who are interested in: (1) conducting research related to the safety evaluation of various frame structures; and (2) seeking for a job position with required professional skills on design, modeling, analysis, and computer programming.
CIV E 661 Dynamics of Structures (Winter Term)
This course aims to cover both the dynamic problem formulation (using Newtonian mechanics and analytical mechanics) and various solution algorithms for free vibration (i.e., eigenvalue) and forced vibration (i.e., closed-form analytical solutions, approximate and numerical solutions, frequency-domain solutions). It is primarily designed for graduate students, who are interested in dynamic behavior of discrete or continuous systems.
CIV E 779 Structural Reliability (Winter Term)
This course aims to cover both the theoretical and computational aspects of modern structural reliability and risk analysis. It is primarily designed for graduate students, who are interested in: (1) seeking for a deeper understanding of design standards or codes with a probabilistic basis; (2) conducting research on solving various engineering problems in the face of uncertainty; and (3) seeking a career in engineering risk.
Teaching at other universities:
2018/06/04 - 2018/06/11, Guest Instructor, Peking University, Beijing, China
Department: The State Key Laboratory for Turbulence and Complex Systems (LTCS), College of Engineering
Course Title: Structural Reliability Methods (I)
Course Level: Graduate
2010/09/22 - 2010/12/10, Instructor, University of California, San Diego, US
Department: Structural Engineering
Course Title: SE 125: Statistics, Probability, and Reliability Analysis
Course Level: Undergraduate
2012/11/10 -2012/12/10, Assistant Teacher, University of Pavia, ROSE School, Pavia, Italy
Course Title: Seismic Response and Nonlinear Structural Analysis
Course Level: Graduate